Control of an Uncertain Robot Manipulator Using an Observation-based Modified Fuzzy Sliding Mode Controller

TayebiHaghighi, Shahnaz; Piltan, Farzin; Kim, Jong‐Myon

doi:10.5815/ijisa.2018.03.05

Cited by 12 publications

(3 citation statements)

References 13 publications

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“…Thus, it is assumed that the exact kinematics and Jacobian matrix of the manipulator are known [7,26]. Other approaches in the literature like in [27][28][29][30][31] have avoided the complexity of working with the inverse kinematic problem by controlling the robot manipulator in the joint space instead of the task space.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

2020

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The problem of inverse kinematics is essential to consider while dealing with the robot’s mechanical structure in almost all applications. Since the solution of the inverse kinematics problem is very complex, many research efforts have been working towards getting the approximate solution of this problem. However, for some applications, working with the approximate robot’s model is neither sufficient nor efficient. In this paper, an adaptive inverse kinematics methodology is developed to solve the inverse kinematics problem in such a way that compensate for unknown uncertainty in the Jacobian matrix of the serial kinematic chain robot manipulators. The proposed methodology is based on continuous second order sliding mode strategy (CSOSM-AIK). The salient advantage of the CSOSM-AIK approach is that it does not require the availability of the kinematics model or Jacobian matrix of the robot manipulators from joint space variables to Cartesian space variables. The global stability of the closed-loop system with CSOSM-AIK methodology is proven using the Lyapunov theorem. In order to demonstrate the robustness and effectiveness of the proposed methodology, some simulations are conducted.

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Section: Introductionmentioning

confidence: 99%

An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

2020

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“…However, PID controllers cannot satisfy the accuracy requirements for certain industry cases, prompting the development of different control techniques. Both sliding-mode controllers (SMCs) and modified SMCs are commonly used control schemes owing to their stability and robustness (Tayebihaghighi et al, 2018). A sliding mode controller was Engenharia Agrícola, Jaboticabal, v.40, n.2, p.215-222, mar./apr.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Sliding-Mode Temperature-Control System for Soaking and Germination of Rice Seeds

Zhou

Chunying

2020

Eng. Agríc.

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The soaking and germination process of rice seeds is the starting point in rice cultivation in cold regions and has a significant effect on grain yield. Efficient techniques for controlling the water temperature in the seed tank are required to enhance germination quality. This paper introduces a fuzzy theory for designing a fuzzy logic-based sliding mode controller (SMC) system for a rice seed soaking and germination device. The proposed system was theoretically and experimentally investigated to determine the efficiency of the soaking temperature-control system. A modified fuzzy SMC based on exponent approaching law is also presented for optimizing the proposed controller. A proportional integral derivative (PID) controller was designed to identify and compare the advantages of the proposed controllers. A comparative study of the computer simulation demonstrates that the performance of fuzzy SMC and modified fuzzy SMC are acceptable, and that both SMCs are superior to the PID controller. Furthermore, compared with the fuzzy SMC system, a reduction in electric energy consumption was observed for the modified fuzzy SMC. Moreover, both SMCs yielded similar soaking qualities.

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“…However, for nonlinear perturbed complex systems with uncertainties, FLSs cannot guarantee the global stability of the closed-loop system [10]. To overcome this problem, many researchers have tried to combine FLSs with other advanced robust methods to achieve good performance, such as SMC, adaptive control, H ∞ technique and neural network [11][12][13][14][15][16]. In [17], the authors have proposed an adaptive sliding mode controller for systems with actuator saturation to guarantee that the closed-loop system is uniformly ultimately bounded.…”

Section: Introductionmentioning

confidence: 99%

A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics

et al. 2018

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In this paper, in order to achieve the best tracking control of a class of multi-input multi-output (MIMO) nonlinear systems with unknown dynamics and unknown disturbances, a new robust adaptive interval type-2 fuzzy sliding mode control law (AIT2-FSMCL) has been proposed. Based on developing interval type-2 fuzzy local models for some operating points of the controlled system, an interval type-2 fuzzy logic system (IT2-FLS) has been designed to better estimate the unknown nonlinear dynamics of the studied system. Then, to enhance the tracking control performance and ensure the system robustness in the presence of approximation errors, parameter variations, un-modelled dynamics and external disturbances, a new AIT2-fuzzy sliding mode system (AIT2-FSMS), has been introduced. In order to avoid the chattering phenomenon while keeping the system performance, the AIT2-FSMS uses three AIT2-fuzzy logic systems (AIT2-FLSs) to estimate the optimal gains of the AIT2-FSMCL. The adaptation laws have been derived using the Lyapunov stability approach. The mathematical proof shows that the closed-loop system with the proposed control approach is globally asymptotically stable. Finally, the proposed design method is applied to a two-link robot arm to validate the effectiveness of the proposed control approach.

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Control of an Uncertain Robot Manipulator Using an Observation-based Modified Fuzzy Sliding Mode Controller

Cited by 12 publications

References 13 publications

An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

An Adaptive Second Order Sliding Mode Inverse Kinematics Approach for Serial Kinematic Chain Robot Manipulators

Fuzzy Sliding-Mode Temperature-Control System for Soaking and Germination of Rice Seeds

A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics

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